CLEAR Lab

CLEAR Lab

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members

Arash

Published:

PhD

Ashley

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PhD

Aura

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PhD

Jeff

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Faculty

Jose

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Masters

Katia

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Undergraduate

Kyle

Published:

PhD

Vishal

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PhD

portfolio

projects

Automated Cloud Native Consulting

Published:

The rapidly growing interest in cloud native applications means more users than ever are needing guidance on how to design and deploy their systems. The Cloud Native Computing Foundation (CNCF) has developed a landscape map that provides the most current collection of both open source and proprietary tools and services, but the breadth of options and the complex relationships between various tools and services can be quite overwhelming. Most users interested in exploring the cloud native space will need to hire an experienced consultant to guide them through the choices, but this can be both cost prohibitive and logistically challenging. Our goal is to automate this consulting process and enable users to make intelligent, informed decisions about their architecture design and then deploy the architecture for immediate use.

Classical to Quantum Encoding

Published:

My research project is based on engineering the encoding of the classical data in a quantum computer for classification in a quantum model.

Development of Enhanced Network Framework Using DTN

Published:

My current project investigates the use cases for a Delay Tolerant Network (DTN) architecture to enhance capabilities in classical networking models. DTNs are used to ensure reliable data delivery in a network of nodes that can exhibit delay, disruption, or disconnection. Coupling this framework with classical networking models, that exhibit disruption in an ever increasing connected world, is investigated to understand tradeoffs with introducing a DTN framework.

publications

Paper Title Number 2

Published in Journal 1, 2010

This paper is about the number 2. The number 3 is left for future work.

Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).

Paper Title Number 3

Published in Journal 1, 2015

This paper is about the number 3. The number 4 is left for future work.

Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).

Classification of Arrhythmias with Inter and Intra Patient Paradigms Using Deep Learning

Published in Journal of Health Informatics, 2021

Classification of cardiac arrhythmia from the morphology of an electrocardiogram signal (ECG) using Deep Learning techniques. Method: We propose a two-level hierarchical classifier. The first level classifies normal and abnormal heartbeats, and the second deals with the multi class identification of the abnormal beats. The classifier is a convolutional neural network architecture (CNN) employed in feature extraction and classification of ECG signal. Results: The method was evaluated on the MIT dataset on the intra-patient and inter-patient paradigms, achieving average accuracy of 98.52% and 90.39%, respectively. Conclusion: The hierarchical method shows improvement on the classification of cardiac arrhythmia, especially on the minority classes, in both paradigms

Recommended citation: Passo, Sthefanie Jofer Gomes. (2021). "Classification of Arrhythmias with Inter and Intra Patient Paradigms Using Deep Learning." Journal of Health Informatics. http://academicpages.github.io/files/Classification-of-Arrhythmias-with-Inter-and-Intra-Patient-Paradigms-Using-Deep-Learning.pdf

Published in , 2024

Published in , 2024

reading

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 3

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

tutorials